{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "neural-puzzle",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "spoken-anaheim",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_man=pd.read_excel('D:/拉钩/拉勾/拉勾/作业/python/matplotlib/matplotlib作业/体测分数_男生.xls')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "fifteen-mattress",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_women=pd.read_excel('D:/拉钩/拉勾/拉勾/作业/python/matplotlib/matplotlib作业/体测分数_女生.xls')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "enhanced-inclusion",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      优\n",
       "1      优\n",
       "2      优\n",
       "3      优\n",
       "4      中\n",
       "      ..\n",
       "472    优\n",
       "473    优\n",
       "474    中\n",
       "475    优\n",
       "476    差\n",
       "Name: 男1000米跑, Length: 477, dtype: category\n",
       "Categories (3, object): ['差' < '中' < '优']"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x=pd.cut(df_man['男1000米跑'],bins=3,labels=['差','中','优'])\n",
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "significant-piano",
   "metadata": {},
   "outputs": [],
   "source": [
    "x=x.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "periodic-wiring",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "优    261\n",
       "中    195\n",
       "差     21\n",
       "Name: 男1000米跑, dtype: int64"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "western-short",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_=plt.pie(x,labels=x.index,autopct='%0.1f%%',textprops={'family':'STKaiti','fontsize':20})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "pleasant-punishment",
   "metadata": {},
   "outputs": [],
   "source": [
    "x=pd.cut(df_man['男引体'],bins=3,labels=['差','中','优'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "legal-faculty",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      差\n",
       "1      差\n",
       "2      差\n",
       "3      差\n",
       "4      中\n",
       "      ..\n",
       "472    差\n",
       "473    差\n",
       "474    中\n",
       "475    中\n",
       "476    差\n",
       "Name: 男引体, Length: 477, dtype: category\n",
       "Categories (3, object): ['差' < '中' < '优']"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "fatty-factor",
   "metadata": {},
   "outputs": [],
   "source": [
    "x=x.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "right-lincoln",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_=plt.pie(x,labels=x.index,autopct='%0.1f%%',textprops={'family':'STKaiti','fontsize':20})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "august-samuel",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "80     102\n",
       "76      72\n",
       "85      66\n",
       "78      61\n",
       "90      41\n",
       "74      37\n",
       "0       33\n",
       "72      32\n",
       "68      27\n",
       "70      25\n",
       "95      24\n",
       "100     18\n",
       "40      11\n",
       "66      10\n",
       "50      10\n",
       "64       6\n",
       "62       5\n",
       "60       5\n",
       "30       4\n",
       "20       3\n",
       "10       1\n",
       "Name: 女800米跑分数, dtype: int64"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x=df_women['女800米跑分数'].value_counts()\n",
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "earlier-bench",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 37.,  15., 157., 384.]),\n",
       " array([  0.,  25.,  50.,  75., 100.]),\n",
       " <BarContainer object of 4 artists>)"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(df_women.女800米跑分数,bins=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "sporting-cameroon",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 19.,  10., 416., 148.]),\n",
       " array([  0.,  25.,  50.,  75., 100.]),\n",
       " <BarContainer object of 4 artists>)"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(df_women.女跳远分数,bins=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "flexible-hammer",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "68     94\n",
       "60     81\n",
       "80     59\n",
       "62     54\n",
       "70     50\n",
       "74     38\n",
       "64     38\n",
       "72     33\n",
       "85     29\n",
       "78     26\n",
       "66     25\n",
       "76     18\n",
       "0      17\n",
       "40      9\n",
       "90      8\n",
       "100     6\n",
       "50      3\n",
       "20      2\n",
       "95      2\n",
       "30      1\n",
       "Name: 女跳远分数, dtype: int64"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_women.女跳远分数.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "shared-tenant",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "def convert(x):\n",
    "    if x <= 16.4:\n",
    "        return('低体重')\n",
    "    elif 16.5< x <23.2:\n",
    "        return('正常')\n",
    "    elif 23.3<x<26.3:\n",
    "        return('超重')\n",
    "    else:\n",
    "        return('肥胖')\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "matched-armenia",
   "metadata": {},
   "outputs": [],
   "source": [
    "x=df_man.BMI.transform(convert)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "musical-repeat",
   "metadata": {},
   "outputs": [],
   "source": [
    "x=x.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "interpreted-portugal",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "def convert1(x):\n",
    "    if x <= 16.4:\n",
    "        return('低体重')\n",
    "    elif 16.5< x <22.7:\n",
    "        return('正常')\n",
    "    elif 22.8<x<25.2:\n",
    "        return('超重')\n",
    "    else:\n",
    "        return('肥胖')\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "behavioral-crash",
   "metadata": {},
   "outputs": [],
   "source": [
    "y=df_women.BMI.transform(convert)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "every-worcester",
   "metadata": {},
   "outputs": [],
   "source": [
    "y=y.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "id": "crazy-burlington",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1c1e61249a0>"
      ]
     },
     "execution_count": 127,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.rcParams['font.family']='STKaiti'\n",
    "plt.rcParams['font.size']=18\n",
    "plt.figure(figsize=(9,9))\n",
    "_=plt.pie(x,radius=1,#autopct='%0.2f%%',\n",
    "          #labels=x.index,\n",
    "          colors=['tomato','yellow','blue','green']\n",
    "       )\n",
    "_=plt.pie(y,\n",
    "       radius=0.7,\n",
    "       #autopct='%0.2f%%',\n",
    "       labels=y.index,\n",
    "       colors=['tomato','yellow','blue','green'],\n",
    "       wedgeprops={'linewidth':5,\n",
    "                  'width':0.7,\n",
    "                  'edgecolor':'white'})\n",
    "plt.legend(['正常','超重','肥胖','低体重'],ncol=2,loc=3)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "adverse-elements",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.2"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
